package com.tencent.supersonic.headless.chat.mapper;

import com.tencent.supersonic.common.config.ParameterConfig;
import com.tencent.supersonic.common.pojo.Parameter;
import org.springframework.stereotype.Service;

@Service("HeadlessMapperConfig")
public class MapperConfig extends ParameterConfig {

    public static final Parameter MAPPER_DETECTION_SIZE =
            new Parameter("s2.mapper.detection.size", "8",
                    "一次探测返回结果个数",
                    "在每次探测后, 将前后缀匹配的结果合并, 并根据相似度阈值过滤后的结果个数",
                    "number", "Mapper相关配置");

    public static final Parameter MAPPER_DETECTION_MAX_SIZE =
            new Parameter("s2.mapper.detection.max.size", "20",
                    "一次探测前后缀匹配结果返回个数",
                    "单次前后缀匹配返回的结果个数",
                    "number", "Mapper相关配置");

    public static final Parameter MAPPER_NAME_THRESHOLD =
            new Parameter("s2.mapper.name.threshold", "0.3",
                    "指标名、维度名文本相似度阈值",
                    "文本片段和匹配到的指标、维度名计算出来的编辑距离阈值, 若超出该阈值, 则舍弃",
                    "number", "Mapper相关配置");

    public static final Parameter MAPPER_NAME_THRESHOLD_MIN =
            new Parameter("s2.mapper.name.min.threshold", "0.25",
                    "指标名、维度名最小文本相似度阈值",
                    "指标名、维度名相似度阈值在动态调整中的最低值",
                    "number", "Mapper相关配置");

    public static final Parameter MAPPER_DIMENSION_VALUE_SIZE =
            new Parameter("s2.mapper.value.size", "1",
                    "一次探测返回维度值结果个数",
                    "在每次探测后, 将前后缀匹配的结果合并, 并根据相似度阈值过滤后的维度值结果个数",
                    "number", "Mapper相关配置");

    public static final Parameter MAPPER_VALUE_THRESHOLD =
            new Parameter("s2.mapper.value.threshold", "0.5",
                    "维度值文本相似度阈值",
                    "文本片段和匹配到的维度值计算出来的编辑距离阈值, 若超出该阈值, 则舍弃",
                    "number", "Mapper相关配置");

    public static final Parameter MAPPER_VALUE_THRESHOLD_MIN =
            new Parameter("s2.mapper.value.min.threshold", "0.3",
                    "维度值最小文本相似度阈值",
                    "维度值相似度阈值在动态调整中的最低值",
                    "number", "Mapper相关配置");

    public static final Parameter EMBEDDING_MAPPER_MIN =
            new Parameter("s2.mapper.embedding.word.min", "4",
                    "用于向量召回最小的文本长度",
                    "为提高向量召回效率, 小于该长度的文本不进行向量语义召回",
                    "number", "Mapper相关配置");

    public static final Parameter EMBEDDING_MAPPER_MAX =
            new Parameter("s2.mapper.embedding.word.max", "5",
                    "用于向量召回最大的文本长度",
                    "为提高向量召回效率, 大于该长度的文本不进行向量语义召回",
                    "number", "Mapper相关配置");

    public static final Parameter EMBEDDING_MAPPER_BATCH =
            new Parameter("s2.mapper.embedding.batch", "50",
                    "批量向量召回文本请求个数",
                    "每次进行向量语义召回的原始文本片段个数",
                    "number", "Mapper相关配置");

    public static final Parameter EMBEDDING_MAPPER_NUMBER =
            new Parameter("s2.mapper.embedding.number", "5",
                    "批量向量召回文本返回结果个数",
                    "每个文本进行向量语义召回的文本结果个数",
                    "number", "Mapper相关配置");

    public static final Parameter EMBEDDING_MAPPER_THRESHOLD =
            new Parameter("s2.mapper.embedding.threshold", "0.99",
                    "向量召回相似度阈值",
                    "相似度小于该阈值的则舍弃",
                    "number", "Mapper相关配置");

    public static final Parameter EMBEDDING_MAPPER_THRESHOLD_MIN =
            new Parameter("s2.mapper.embedding.min.threshold", "0.9",
                    "向量召回最小相似度阈值",
                    "向量召回相似度阈值在动态调整中的最低值",
                    "number", "Mapper相关配置");

    public static final Parameter EMBEDDING_MAPPER_ROUND_NUMBER =
            new Parameter("s2.mapper.embedding.round.number", "10",
                    "向量召回最小相似度阈值",
                    "向量召回相似度阈值在动态调整中的最低值",
                    "number", "Mapper相关配置");

}
